Non-contact coal feeder automatic metering calibration method

Abstract

The application provides a non-contact coal feeder automatic metering calibration method, and belongs to the technical field of continuous material conveying dynamic metering, which can at least partially solve the problems of existing technology, such as serious temperature drift of a strain type weighing sensor under high temperature and high dust working conditions of a coal feeder, dynamic mismatch of speed-weight signals, and the need for shutdown operation for calibration. The application comprises the following steps: projecting a light curtain on material on a conveying belt and collecting sequence cross-section images; determining the moving length of the belt based on encoder pulses; obtaining cross-section area by extracting the edge of the cross-section image and integrating the area; calculating the cumulative material weight based on the cross-section area, the moving length, the material density and the calibration coefficient; obtaining the calibration sample reference weight and calculating the calibration coefficient when the calibration trigger condition is met; and updating the subsequent metering result based on the calibration coefficient. The application realizes non-contact continuous dynamic metering and online automatic calibration.

Description

Technical Field

[0001] This invention relates to the field of dynamic metering technology for continuous conveying equipment, and specifically to a non-contact automatic metering calibration method for a coal feeder. Background Technology

[0002] The coal feeder is a core piece of equipment in the boiler fuel supply system of a thermal power plant, and its metering accuracy directly affects the unit's coal consumption analysis and economic operation optimization. Currently, the weighing electronic belt scales widely used in coal feeder systems mainly use resistance strain gauge sensors as the core weighing component, combined with speed sensors to achieve dynamic metering.

[0003] However, due to factors such as coal flow friction and equipment heat dissipation, the internal temperature of the coal feeder often reaches instantaneous levels of 70-80°C. In this environment of alternating temperature changes, strain gauge load cells experience significant temperature drift, leading to distortion and fluctuations in the output signal. Furthermore, strain gauge sensors rely on a structure where resistance strain gauges are bonded to a steel body. Under continuous vibration and alternating temperature conditions, the bonded layer is prone to micro-cracks or even detachment, causing a decrease in weighing sensitivity and zero-point drift. Typically, accuracy becomes difficult to maintain after a period of operation.

[0004] Furthermore, under variable frequency speed control conditions, traditional speed sensors exhibit a dynamic matching time difference between the pulse signal output by the speed sensor and the millivolt signal collected by the weighing sensor when the feeder belt speed changes frequently and instantaneously. This leads to a further increase in the measured error when speed changes are frequent. Traditional chain code or hanging code calibration methods require machine shutdown, which is labor-intensive, time-consuming, and the reliability of the calibrated data decays over time, making it difficult to meet the online calibration requirements of modern production management.

[0005] Therefore, how to eliminate the temperature drift and mechanical fatigue defects of strain gauge load cells, achieve synchronous matching between speed and image acquisition under variable frequency speed regulation conditions, and complete online automatic calibration without stopping the machine are the core problems that urgently need to be solved in the field of dynamic metering technology for coal feeders. Summary of the Invention

[0006] The present invention aims to solve at least one of the technical problems existing in the prior art, and to provide a non-contact automatic metering and calibration method for coal feeders.

[0007] To achieve the above objectives, the present invention provides a non-contact automatic metering calibration method for a coal feeder, comprising: Step S1: Project a light curtain onto the material on the coal feeder conveyor belt and simultaneously acquire sequential cross-sectional images of the material; Step S2: Based on the pulse signal output by the encoder installed on the driven drum of the coal feeder, determine the belt movement length between two adjacent frames of the sequence cross-sectional images; Step S3: Extract edge contours from each frame of the sequence cross-sectional image and integrate to calculate the cross-sectional area, thereby obtaining the cross-sectional area corresponding to each frame of the sequence cross-sectional image; Step S4: Based on the cross-sectional area, the belt movement length, the material density, and the calibration coefficient, calculate the cumulative material weight according to the volume-weight conversion relationship; Step S5: When the preset calibration trigger condition is met, release the calibration coal sample and obtain the reference weight of the calibration coal sample. Calculate a new calibration coefficient based on the reference weight and the cumulative volume within the corresponding time period. Step S6: Replace the current calibration coefficient with the new calibration coefficient to update the measurement result of the cumulative material weight.

[0008] Furthermore, in step S1, a fan-shaped light curtain is projected onto the material on the conveyor belt using a near-infrared light source, the plane of which is perpendicular to the surface of the conveyor belt; simultaneously, an image acquisition device is triggered to acquire the sequential cross-sectional image formed by the material under the illumination of the fan-shaped light curtain.

[0009] Further, in step S2, the belt movement length Calculate using the following formula: ; in, The effective diameter of the driven roller is... The number of pulses output per revolution of the encoder. This is the pulse frequency multiplication factor. The encoder count increment is the time interval between the acquisition times of two adjacent frames of the sequence cross-sectional image.

[0010] Further, in step S3, subpixel edge detection and polygon approximation are sequentially performed on each frame of the sequence cross-sectional image to obtain the vertex coordinates of the cross-sectional contour; based on the vertex coordinates of the cross-sectional contour, the cross-sectional area is calculated according to the following formula. : ; in, and These are the pixel equivalents for the horizontal and vertical directions of the image, respectively. For the first The number of vertices of a cross-sectional profile. For the first The first section The coordinates of the contour vertices.

[0011] Further, in step S4, the cumulative material weight Calculate using the following formula: ; in, The calibration coefficient is... The density of the material is... For the first The cross-sectional area corresponding to the sequence cross-sectional image of the frame. For the first Frame and the The belt movement length between frames, The number of cross-sectional frames included in the cumulative total.

[0012] Further, in step S5, obtaining the reference weight of the calibration coal sample includes: controlling the silo gate to release the calibration coal sample, so that the calibration coal sample passes sequentially through the upstream and downstream weighing platforms arranged in series, and obtaining the upstream weighing value respectively. and downstream weighing value The coal loss compensation amount is calculated based on the upstream and downstream weighing values. : ; When the absolute value of the coal loss compensation is greater than the preset compensation threshold, the upstream weighing value is used. The reference weight is used as the reference weight, and the new calibration coefficient is calculated according to the following formula. : ; in, This represents the number of cross-sectional frames included in the cumulative calculation during the calibration period.

[0013] Furthermore, in step S6, the replacement of the current calibration coefficient with the new calibration coefficient adopts a smooth update strategy: ; in, The calibration coefficients are as described above. The new calibration coefficient is calculated in step S5. To ensure smooth coefficient updates.

[0014] Furthermore, the preset calibration trigger condition includes at least one of the following conditions: The continuous running time reaches the preset calibration cycle; The changes in the coal quality parameters of the coal fed into the furnace exceed the preset threshold for coal type changes; The continuous measurement deviation exceeds the preset deviation threshold and continues for a preset duration.

[0015] Furthermore, the method also includes: The operating environment temperature of the image acquisition device and the light source is controlled to a preset constant temperature range to eliminate the effects of temperature drift; and The deviation of the conveyor belt is detected in real time. When the deviation exceeds a preset deviation threshold, the coordinate offset of the acquisition area of ​​the sequence cross-sectional image is corrected.

[0016] Furthermore, in step S1, the light curtain adopts a primary and backup redundant light source structure. When the output intensity of the primary light source decays to below a preset intensity threshold, it automatically switches to the backup light source.

[0017] The beneficial effects of this invention are as follows: This invention projects a light curtain onto the material on the conveyor belt and acquires sequential cross-sectional images. It uses a non-contact optical profile scanning principle to replace the traditional strain gauge weighing sensor, fundamentally eliminating the temperature drift problem in environments with alternating temperature changes and the defect of decreased sensitivity caused by the cracking and detachment of the resistance strain gauge adhesive layer under continuous vibration conditions.

[0018] This invention determines the belt movement length between adjacent cross-sectional images based on encoder pulse signals, converts speed into length, and achieves synchronization between image acquisition and belt movement through hardware triggering, eliminating the error caused by the dynamic matching time difference between pulse signals and millivolt signals in traditional speed sensors under variable frequency speed regulation conditions.

[0019] This invention achieves online automatic calibration without downtime by automatically releasing the calibration coal sample and obtaining the benchmark weight when the preset calibration trigger conditions are met, and using the series weighing of two scales to calculate the coal loss compensation and update the calibration coefficient. This overcomes the shortcomings of traditional weight-based calibration methods, such as downtime operation, high labor intensity, and long time consumption. Attached Figure Description

[0020] Figure 1 This is an overall flowchart of the non-contact automatic metering and calibration method for coal feeders according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the image acquisition and light curtain projection device according to an embodiment of the present invention; Figure 3 This is a block diagram illustrating the working principle of the speed synchronization conversion module according to an embodiment of the present invention. Figure 4 This is a flowchart illustrating the core algorithm processing in an embodiment of the present invention. Figure 5 This is a schematic diagram of the automatic physical calibration system according to an embodiment of the present invention; Figure 6 This is a diagram of a multi-level failure protection architecture according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and beneficial effects of this application clearer, the following detailed description, in conjunction with the accompanying drawings and specific embodiments, further illustrates this application. It should be understood that the specific embodiments described in this specification are merely for explaining this application and are not intended to limit it.

[0022] The overall technical solution of the non-contact automatic metering and calibration method for coal feeders of the present invention will be described below.

[0023] See Figure 1 The non-contact automatic metering calibration method for coal feeders of the present invention includes steps S1 to S6, and each step will be described in detail below.

[0024] Step S1 involves projecting a light curtain onto the material on the coal feeder conveyor belt and simultaneously acquiring a sequence of cross-sectional images of the material. The light curtain refers to a thin, sheet-like light surface formed in space by optical shaping of a light source, used to project a recognizable cross-sectional outline onto the material. The sequence of cross-sectional images refers to an ordered set of material cross-sectional outline images acquired at multiple consecutive moments as the conveyor belt moves. The light curtain projection and image acquisition are performed synchronously to ensure that each frame of the cross-sectional image corresponds to a specific belt position.

[0025] In this invention, "light curtain" is a higher-level concept for an optical projection structure used to form a cross-sectional profile on the surface of a material. The light curtain can be implemented, but is not limited to, the following: a fan-shaped near-infrared light curtain formed by a near-infrared semiconductor laser array shaped by a cylindrical lens; a line-structured light curtain projected by a visible light structured light projector; and a fan-shaped white light curtain formed by an LED array light source through a cylindrical lens. The commonality among different types of light curtains is that they can all form a recognizable optical cross-sectional profile on the surface of the material, enabling the image acquisition device to obtain the cross-sectional profile information of the material. The common applicable conditions among the above-mentioned different light curtain implementation methods are: the wavelength of the light source should match the response band of the image sensor, and the thickness of the light curtain should meet the clarity requirements of the cross-sectional profile.

[0026] In a preferred embodiment, a fan-shaped light curtain is projected onto the material on the conveyor belt using a near-infrared light source, the plane of which is perpendicular to the surface of the conveyor belt. The wavelength range of the near-infrared light source is 800nm ​​to 1000nm, within which the light beam has better penetration ability than visible light into the dusty and water vapor environment inside the coal feeder. An image acquisition device is synchronously triggered to acquire the sequence of cross-sectional images formed by the material under the illumination of the fan-shaped light curtain. The image acquisition device can be, but is not limited to, the following: an area-array CMOS industrial camera, an area-array CCD industrial camera, or a line-array scanning camera. The commonality among these different devices is that they all possess sufficient spatial resolution and frame rate to acquire clear images of the material's cross-sectional contour during conveyor belt movement.

[0027] Step S2 involves determining the belt movement length between two adjacent frames of the sequence cross-sectional images based on the pulse signal output by the encoder installed on the driven drum of the coal feeder. The encoder is installed on the shaft end of the driven drum of the coal feeder and rotates synchronously with the driven drum. The encoder outputs a fixed number of pulse signals per revolution. By converting the pulse count increment between the acquisition times of two adjacent frames, the actual physical length of belt movement within that time period can be accurately obtained. The encoder can be, but is not limited to, the following types: incremental rotary encoder and absolute rotary encoder. The common feature of different types of encoders is that they can all convert the rotational motion of the driven drum into a pulse electrical signal proportional to the rotation angle, thereby determining the belt movement amount by counting the pulses.

[0028] In a preferred embodiment, the pulse signal output by the encoder is frequency-multiplied by a signal conditioning circuit and then input to a timing controller. When the timing controller detects the rising edge of the encoder pulse, it latches the current counter value and synchronously sends a hardware trigger signal to the image acquisition device, achieving microsecond-level synchronization between the image acquisition time and the encoder pulse. The belt movement length... Calculate using the following formula: ; in, The effective diameter of the driven roller is... The number of pulses output per revolution of the encoder. This is the pulse frequency multiplication factor. The encoder count increment is the time interval between the acquisition times of two adjacent frames of the sequence cross-sectional image.

[0029] Step S3 involves extracting the edges and integrating the area of ​​each frame of the sequence of cross-sectional images to obtain the cross-sectional area corresponding to each frame. "Edge extraction" refers to the higher-level concept of image processing operations that extract the boundary coordinates of the material contour from the cross-sectional image. Edge extraction can be implemented using, but is not limited to, the following algorithms: sub-pixel Canny operator edge detection, Sobel operator gradient edge detection, Laplacian operator second-order differential edge detection, and phase-consistent edge detection. The commonality among these algorithms is that they can all extract the set of boundary coordinate points of the material cross-sectional contour from the grayscale image. "Area integration" refers to the numerical integration operation of calculating the area enclosed by the closed contour based on the extracted contour boundary coordinates. This can be achieved using the analytical formula for the area of ​​polygon vertex coordinates, the numerical trapezoidal integral method, or Green's formula integration method.

[0030] In a preferred embodiment, subpixel edge detection and polygon approximation are sequentially performed on each frame of the sequence of cross-sectional images to obtain the vertex coordinates of the cross-sectional contour. Subpixel edge detection improves the accuracy of contour point localization to the subpixel level through grayscale gradient subpixel interpolation. Polygon approximation uses a recursive segmentation algorithm to approximate continuous contour curves into polygons, reducing computational load while preserving contour features. Based on the vertex coordinates of the cross-sectional contour, the cross-sectional area is calculated according to the polygon area formula. : ; in, and These are the pixel equivalents for the horizontal and vertical directions of the image, respectively. For the first The number of vertices of a cross-sectional profile. For the first The first section The coordinates of each contour vertex. The pixel equivalent is obtained through calibration, converting the pixel coordinates into physical dimensions.

[0031] Step S4 involves calculating the cumulative material weight based on the cross-sectional area, the belt travel length, the material density, and the calibration coefficient, according to the volume-weight conversion relationship. The physical meaning of the volume-weight conversion relationship is: multiplying the sequential cross-sectional area by the corresponding belt travel length to obtain a micro-volume, summing all micro-volumes to obtain the cumulative volume, and then multiplying by the material density and the calibration coefficient to obtain the material weight. The cumulative material weight... Calculate using the following formula: ; in, The calibration coefficient is... The density of the material is... For the first The cross-sectional area corresponding to the sequence cross-sectional image of the frame. For the first Frame and the The belt movement length between frames, The number of cross-sectional frames participating in the accumulation. The calibration coefficient. It comprehensively reflects the impact of factors such as bulk density fluctuation, particle size distribution, moisture content and coal impact on measurement accuracy, and is updated online through automatic calibration closed loop in steps S5 and S6.

[0032] Step S5 involves releasing the calibration coal sample and obtaining its baseline weight when the preset calibration trigger condition is met. A new calibration coefficient is then calculated based on the baseline weight and the cumulative volume over the corresponding time period. The "preset calibration trigger condition" is a higher-level concept used to determine whether to initiate the automatic calibration process. The calibration trigger condition can be implemented, but is not limited to, the following: timed triggering, i.e., automatically triggered when the continuous running time reaches a preset calibration cycle; coal type change triggering, i.e., automatically triggered when the coal quality parameters of the coal fed into the furnace change exceed a preset coal type change threshold; and deviation accumulation triggering, i.e. automatically triggered when the continuous measurement deviation exceeds a preset deviation threshold and continues for a preset duration. The commonality of the different trigger conditions is that they all automatically initiate the calibration process based on whether a certain indicator of the operating status exceeds a preset threshold, without requiring manual intervention.

[0033] In a preferred embodiment, obtaining the reference weight of the calibration coal sample includes: controlling the silo gate to release the calibration coal sample, so that the calibration coal sample passes sequentially through an upstream weighing platform and a downstream weighing platform arranged in series, and obtaining the upstream weighing value respectively. and downstream weighing value The upstream weighing platform receives coal samples falling from the silo and measures their static weight. The downstream weighing platform weighs the same coal sample twice, reflecting the weight loss during the descent. The compensation amount for coal loss is calculated based on the upstream and downstream weighing values. : ; The coal drop loss compensation amount is used to quantify the weight loss caused by airflow entrainment, coal sample adhesion, and kinetic energy conversion during the coal drop process. When the absolute value of the coal drop loss compensation amount is greater than a preset compensation threshold, the upstream weighing value is used. The reference weight is used as the reference weight, and the new calibration coefficient is calculated according to the following formula. : ; in, This represents the number of cross-sectional frames included in the cumulative calculation during the calibration period.

[0034] Step S6 involves replacing the current calibration coefficient with the new calibration coefficient to update the measurement result of the subsequent cumulative material weight. The updated calibration coefficient is used for subsequent weight calculations in step S4, thereby forming a complete closed loop of "measurement-calibration-remeasurement".

[0035] In a preferred embodiment, the replacement of the current calibration coefficient with the new calibration coefficient employs a smooth update strategy. This smooth update strategy means that instead of directly replacing the current calibration coefficient with the result of a single calibration, the current value and the new value are weighted and fused to reduce the disturbance of the calibration coefficient by random errors in a single calibration. The smooth update formula is: ; in, The calibration coefficients are as described above. The new calibration coefficients calculated in step S5 To ensure smooth coefficient updates, an alternative implementation could be a direct replacement method, i.e. Alternatively, a batch update method can be adopted, which involves calibrating multiple times, averaging the results, and then replacing the calibrated values. The commonality among these different update methods is that they all feed the newly calculated calibration coefficients back to step S4 for subsequent metrological calculations.

[0036] The above is a description of the overall technical solution of the present invention. The following detailed explanation of each step is provided through specific embodiments.

[0037] Example 1 This embodiment uses a coal feeder configured on a 300MW unit of a thermal power plant as the application object. The conveyor belt of the coal feeder is 800mm wide, the belt speed is adjustable from 0.3m / s to 1.2m / s, the average internal temperature of the coal feeder is 65℃, and the coal dust concentration is about 900mg / m³.

[0038] Step S1: Project a light curtain onto the material on the coal feeder conveyor belt and simultaneously acquire sequential cross-sectional images of the material.

[0039] In this embodiment, a fan-shaped light curtain is projected onto the material on the conveyor belt using a near-infrared light source. The near-infrared light source is an 850nm near-infrared semiconductor laser with an output power of 200mW. After being shaped by a cylindrical mirror, the laser beam forms a fan-shaped light curtain with a thickness of 1.5mm, and the plane of the fan-shaped light curtain is perpendicular to the surface of the conveyor belt. The light source and the image acquisition device are connected as a whole by a rigid bracket and installed 1000mm directly above the conveyor belt.

[0040] The image acquisition device is synchronously triggered to acquire the sequential cross-sectional images of the material formed under the illumination of the fan-shaped light curtain. In this embodiment, the image acquisition device uses a 2048×1536 pixel area array CMOS industrial camera, equipped with a 12mm focal length fixed-focus lens, and the field of view covers the full width of the conveyor belt (800mm) and the maximum height of the coal flow (300mm). The angle between the optical axis of the image acquisition device and the plane of the light curtain is 30°, and the two form a linear intersection area on the surface of the conveyor belt. This area is the effective measurement section for optical contour scanning.

[0041] Step S2: Based on the pulse signal output by the encoder installed on the driven drum of the coal feeder, determine the belt movement length between two adjacent frames of the sequence cross-sectional images.

[0042] In this embodiment, the encoder is an incremental rotary encoder, installed on the non-drive shaft end of the driven drum of the coal feeder, outputting 1024 pulses per revolution. The encoder shaft is connected to the driven drum shaft via a flexible coupling. The signal conditioning circuit performs quadruple frequency processing on the AB phase pulses output by the encoder, increasing the resolution to 4096 pulses / revolution.

[0043] The timing controller is implemented based on hardware logic and internally configured with a 50MHz crystal oscillator to generate a time base. When the rising edge of the encoder pulse is detected, a hardware trigger signal is sent to the image acquisition device within 1μs, and the current counter value is latched simultaneously. In this embodiment, the effective diameter of the driven roller... = 400mm, number of encoder output pulses per revolution = 1024, frequency harmonics = 4. The belt movement length corresponding to a single pulse is mm.

[0044] The belt travel length Calculate using the following formula: ; in The encoder count increment is used between two adjacent image frames. At a belt speed of 0.3 m / s, approximately one image frame is acquired every 33 pulses, corresponding to a belt movement length of approximately 10 mm; at a belt speed of 1.2 m / s, approximately one image frame is acquired every 130 pulses, corresponding to a belt movement length of approximately 40 mm.

[0045] Step S3: Extract the edges of the sequence cross-sectional image of each frame and integrate the area to obtain the cross-sectional area corresponding to each frame of the sequence cross-sectional image.

[0046] In this embodiment, the processing flow for each frame of the sequence cross-sectional image includes, in sequence: distortion correction, adaptive threshold segmentation, subpixel edge detection, and polygon approximation.

[0047] Distortion correction parameters were pre-calibrated using the Zhang Zhengyou calibration method. Adaptive threshold segmentation employed a bimodal method based on gray-level histograms to automatically calculate the threshold. The gray-level histogram of the current frame image was statistically analyzed, and two peaks were identified, corresponding to the concentrated gray-level values ​​of the dark coal area and the bright belt area, respectively. The minimum gray-level point between the two peaks was calculated as the initial threshold, and an iterative method was used to refine the threshold until convergence.

[0048] Subpixel edge detection uses the Canny operator, with high and low thresholds set at 150 and 50 respectively, achieving a contour point localization accuracy of 0.1 pixels. The extracted contour points are then processed using a polygon approximation algorithm, achieving a high approximation accuracy. = 0.5 pixels, keeping the number of contour vertices between 500 and 2000. The polygon approximation algorithm uses a recursive segmentation method: connect a straight line segment between the start and end points of the contour curve, calculate the perpendicular distance from all points on the contour to this straight line segment, and find the point with the maximum distance and its distance value. ;like Then, the curve is divided into two segments using the point of maximum distance as the dividing point, and the process is recursively executed for each segment; if If the curve segment is not a straight line segment, then the curve segment is replaced by a straight line segment. After the recursion terminates, all the dividing points are the vertices of the polygon.

[0049] The cross-sectional area is calculated based on the vertex coordinates of the cross-sectional profile using the polygon area formula. In this embodiment, the pixel equivalent is determined through calibration. mm / pixel.

[0050] Step S4: Based on the cross-sectional area, the belt moving length, the material density, and the calibration coefficient, calculate the cumulative material weight according to the volume-weight conversion relationship.

[0051] In this embodiment, the bulk density of bituminous coal is used. = 850 kg / m³, calibration factor The initial value was determined to be 1.023 through the initial calibration. The cumulative material weight... Calculate using the following formula: ; Taking a certain metering cycle as an example, continuous data collection = 3000 frames of cross-sectional images, = 0.0588 m³, then the weight of the material is: ; Compared with the actual calibrated weight of 51.00 kg, the error is 0.25%, which meets the measurement accuracy requirement of 0.2% to 0.5%.

[0052] Step S5: When the preset calibration trigger condition is met, release the calibration coal sample and obtain the reference weight of the calibration coal sample. Calculate a new calibration coefficient based on the reference weight and the cumulative volume within the corresponding time period.

[0053] In this embodiment, the preset calibration trigger conditions are set as follows: continuous running time reaches 8 hours, or the change in volatile matter of coal entering the furnace exceeds 5%, or the change in ash content exceeds 3%.

[0054] When the calibration trigger condition is met, the control hopper gate releases the calibration coal sample. The gate opening maintains the coal sample flow rate at 5 to 8 t / h. The required coal quantity for calibration is approximately 500 kg, and the calibration duration is approximately 10 minutes. The calibration coal sample passes sequentially through an upstream weighing platform and a downstream weighing platform arranged in series. Both the upstream and downstream weighing platforms use load cells with a range of 500 kg and an accuracy class of C3. The upstream weighing platform receives the falling coal and weighs it. = 250.00 kg, the weight measured on the downstream weighing platform = 245.50kg, the compensation for coal loss is: ; = 0.018 > 0.01 (preset compensation threshold), triggering calibration coefficient correction. = 250.00 kg as the reference weight, the optical metrological weight value during calibration without correction for calibration factors. = 244.38 kg (this is the optical measurement value), then the new calibration coefficient is: ; Step S6: Replace the current calibration coefficient with the new calibration coefficient to update the measurement result of the cumulative material weight.

[0055] In this embodiment, a smooth update strategy is adopted to smoothly update the coefficients. = 0.3: ; The updated calibration factor of 1.030 is used for weight calculation in subsequent step S4, completing one metrology-calibration closed loop.

[0056] Example 2 This embodiment uses a coal feeder configured on a 600MW unit of a thermal power plant as the application example. The feeder has a conveyor belt width of 1000mm, an adjustable belt speed ranging from 0.2m / s to 1.5m / s, an average internal temperature of 75℃, a coal dust concentration of approximately 1100mg / m³, and burns low-volatile anthracite coal with a bulk density of [missing information]. = 950 kg / m³.

[0057] Step S1: Project a light curtain onto the material on the coal feeder conveyor belt and simultaneously acquire sequential cross-sectional images of the material.

[0058] In this embodiment, the near-infrared light source is a near-infrared semiconductor laser with a wavelength of 940nm and an output power of 300mW. The 940nm wavelength was chosen because this band falls within the water vapor absorption window, offering better penetration in water vapor-containing environments. The fan-shaped light curtain is 2.0mm thick and installed at a height of 1200mm from the conveyor belt surface. The image acquisition device uses a 2448×2048 pixel area array CMOS industrial camera equipped with an 8mm fixed-focus lens, covering a field of view of 1000mm conveyor belt width and a maximum coal flow height of 350mm.

[0059] Step S2: Based on the pulse signal output by the encoder installed on the driven drum of the coal feeder, determine the belt movement length between two adjacent frames of the sequence cross-sectional images.

[0060] In this embodiment, the encoder is an absolute rotary encoder, outputting 2048 pulses per revolution. The effective diameter of the driven roller... = 500mm. The signal conditioning circuit performs a quadruple frequency multiplication on the encoder pulses, with a multiplication factor of 1 / 4. = 4. The belt movement length corresponding to a single pulse is mm.

[0061] Step S3: Extract the edges of the sequence cross-sectional image of each frame and integrate the area to obtain the cross-sectional area corresponding to each frame of the sequence cross-sectional image.

[0062] The image processing flow in this embodiment is the same as in Embodiment 1, including distortion correction, adaptive thresholding, subpixel edge detection, and polygon approximation in sequence. Due to the increased conveyor belt width, the pixel equivalent in this embodiment is determined through calibration. mm / pixel. Subpixel edge detection uses the Canny operator, with high and low thresholds adjusted to 180 and 60 respectively based on the grayscale characteristics of the coal type. Polygon approximation accuracy. = 0.4 pixels.

[0063] Step S4: Based on the cross-sectional area, the belt moving length, the material density, and the calibration coefficient, calculate the cumulative material weight according to the volume-weight conversion relationship.

[0064] In this embodiment, the bulk density of anthracite coal = 950 kg / m³, calibration factor The initial value was determined to be 1.035 through the initial calibration. Taking a certain measurement cycle as an example, continuous data collection... = 5000 frames of cross-sectional images, = 0.1042m³, then the weight of the material is: ; The error is 0.24% compared to the actual calibrated weight of 102.20 kg.

[0065] Step S5: When the preset calibration trigger condition is met, release the calibration coal sample and obtain the reference weight of the calibration coal sample. Calculate a new calibration coefficient based on the reference weight and the cumulative volume within the corresponding time period.

[0066] In this embodiment, the preset calibration trigger conditions are set as follows: continuous operation time reaches 6 hours, or the volatile matter change of the coal fed into the furnace exceeds 3%, or the ash content change exceeds 2%, or the continuous metering deviation exceeds 0.5% and lasts for 30 minutes. Since anthracite varies significantly in type, the calibration frequency is appropriately increased compared to bituminous coal.

[0067] The control silo gate releases the calibrated coal sample, maintaining the coal sample flow rate at 6 to 10 t / h. The upstream weighing platform weighs... =300.00 kg, weighed on the downstream weighing platform = 293.40 kg. The compensation for coal loss is: ; = 0.022>0.01, triggering calibration coefficient correction. The optical weight corresponding to the cumulative volume of optical metrology during calibration is 291.83 kg (taken as...). When = 1.035), then: ; Step S6 employs a smooth update strategy. = 0.25: ; Example 3 This embodiment uses a small coal feeder configured on a 200MW unit of a thermal power plant as the application example. The feeder has a conveyor belt width of 650mm, an adjustable belt speed ranging from 0.1m / s to 0.8m / s, a belt wheelbase of only 2.5m, an average internal temperature of 55℃, a coal dust concentration of approximately 700mg / m³, and burns lignite with a bulk density of [missing information]. = 750 kg / m³.

[0068] Step S1: Project a light curtain onto the material on the coal feeder conveyor belt and simultaneously acquire sequential cross-sectional images of the material.

[0069] In this embodiment, the near-infrared light source is an 850nm near-infrared semiconductor laser with an output power of 150mW. The fan-shaped light curtain is 1.0mm thick and installed 800mm above the conveyor belt surface. The image acquisition device uses a 1280×1024 pixel area array CMOS industrial camera equipped with a 12mm fixed-focus lens. The light curtain adopts a primary and backup redundant light source structure, with the primary and backup light sources installed in parallel and 10mm apart along their optical axes. When the output intensity of the primary light source attenuates to below 80% of its rated value, it automatically switches to the backup light source in less than 100ms.

[0070] Step S2: Based on the pulse signal output by the encoder installed on the driven drum of the coal feeder, determine the belt movement length between two adjacent frames of the sequence cross-sectional images.

[0071] In this embodiment, the effective diameter of the driven roller = 300mm, encoder outputs 512 pulses per revolution, frequency multiplication factor = 4. The belt movement length corresponding to a single pulse is mm.

[0072] Step S3: Extract the edges of the sequence cross-sectional images for each frame and integrate the area to obtain the cross-sectional area corresponding to each frame of the sequence cross-sectional images. The processing flow is the same as in Example 1. The pixel equivalent is determined by calibration. mm / pixel.

[0073] Step S4: Lignite Bulk Density = 750 kg / m³, calibration factor The initial value was determined to be 1.018 through the initial calibration. Taking a certain measurement cycle as an example, continuous data collection... = 2000 frames of cross-sectional images, = 0.0335 m³, then the weight of the material is: ; The error is 0.31% compared to the actual calibrated weight of 25.50 kg.

[0074] Step S5: In this embodiment, the preset calibration trigger condition is set to a continuous running time of 8 hours. Since lignite has relatively stable coal quality, no coal type change trigger condition is set.

[0075] The control silo gate releases the calibration coal sample, which is then weighed on the upstream weighing platform. = 200.00 kg, weighed on the downstream weighing platform =196.80 kg. The compensation for coal loss is: ; = 0.016>0.01, triggering calibration coefficient correction.

[0076] Step S6 employs a smooth update strategy. = 0.3, update calibration coefficient.

[0077] This embodiment also includes environmental protection measures. The working environment of the image acquisition device and the light source is controlled to a preset constant temperature range of (25±2)℃ by a semiconductor cooling temperature control module, with a temperature control accuracy of ±0.5℃. The deviation of the conveyor belt is detected in real time. Linear array sensors are installed on both sides of the conveyor belt to detect the position of the belt edge. When the deviation exceeds a preset deviation threshold of ±5mm, the image offset correction algorithm is activated. Affine transformation is used to correct the coordinate offset of the acquisition area of ​​the sequence cross-sectional image, so that the scanning position is always aligned with the center line of the belt.

[0078] In summary, the embodiments of the present invention have at least the following technical effects: This invention replaces strain gauge load cells with optical profile scanning, completely eliminating the temperature drift problem in environments with alternating temperature changes and the defects of cracking and detachment of the adhesive layer of resistance strain gauges. It achieves continuous dynamic metering accuracy within the range of 0.2% to 0.5% on coal feeders of different capacity units.

[0079] This invention achieves precise conversion of speed into length by synchronizing encoder pulse signals with image acquisition at the hardware level, thus eliminating the dynamic matching time difference between traditional speed sensors and weighing sensors under variable frequency speed control conditions.

[0080] This invention utilizes an automated physical calibration system to perform online calibration without shutting down the system. The calibration process requires no manual intervention, and the calibration frequency can be flexibly set according to operating conditions. The dual-weighing platform series weighing structure quantifies the weight loss during coal feeding, and the smooth update strategy reduces the disturbance of calibration coefficients by random errors in a single calibration.

[0081] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A non-contact automatic metering calibration method for a coal feeder, characterized in that, include: Step S1: Project a light curtain onto the material on the conveyor belt of the coal feeder, and simultaneously acquire sequential cross-sectional images of the material; Step S2: Based on the pulse signal output by the encoder of the driven drum installed on the coal feeder, determine the belt movement length between two adjacent frames of the sequence cross-sectional image; Step S3: Extract edge contours from each frame of the sequence cross-sectional image and integrate to calculate the cross-sectional area, thereby obtaining the cross-sectional area corresponding to each frame of the sequence cross-sectional image; Step S4: Based on the cross-sectional area, the belt movement length, the material density, and the calibration coefficient, calculate the cumulative material weight according to the volume-weight conversion relationship; Step S5: When the preset calibration trigger condition is met, release the calibration coal sample and obtain the reference weight of the calibration coal sample. Calculate a new calibration coefficient based on the reference weight and the cumulative volume within the corresponding time period. Step S6: Replace the current calibration coefficient with the new calibration coefficient to update the measurement result of the cumulative material weight.

2. The non-contact automatic metering calibration method for a coal feeder according to claim 1, characterized in that, In step S1, a fan-shaped light curtain is projected onto the material on the conveyor belt using a near-infrared light source. The plane of the fan-shaped light curtain is perpendicular to the surface of the conveyor belt. Simultaneously, an image acquisition device is triggered to acquire the sequence cross-sectional image formed by the material under the illumination of the fan-shaped light curtain.

3. The non-contact coal feeder automatic metering calibration method according to claim 1, characterized in that, In step S2, the belt movement length Calculate using the following formula: ； in, The effective diameter of the driven roller is... The number of pulses output per revolution of the encoder. This is the pulse frequency multiplication factor. The encoder count increment is the time interval between the acquisition times of two adjacent frames of the sequence cross-sectional image.

4. The non-contact coal feeder automatic metering calibration method according to claim 1, characterized in that, In step S3, subpixel edge detection and polygon approximation are sequentially performed on each frame of the sequence cross-sectional image to obtain the vertex coordinates of the cross-sectional contour; based on the vertex coordinates of the cross-sectional contour, the cross-sectional area is calculated according to the following formula. : ； in, and These are the pixel equivalents for the horizontal and vertical directions of the image, respectively. For the first The number of vertices of a cross-sectional profile. For the first The first section The coordinates of the contour vertices.

5. The non-contact coal feeder automatic metering calibration method according to claim 1, characterized in that, In step S4, the cumulative material weight Calculate using the following formula: ； in, The calibration coefficient is... The density of the material is... For the first The cross-sectional area corresponding to the sequence cross-sectional image of the frame. For the first Frame and the The belt movement length between frames, The number of cross-sectional frames included in the cumulative total.

6. The non-contact coal feeder automatic metering calibration method according to claim 5, characterized in that, In step S5, obtaining the reference weight of the calibration coal sample includes: controlling the silo gate to release the calibration coal sample, so that the calibration coal sample passes sequentially through the upstream and downstream weighing platforms arranged in series, and obtaining the upstream weighing value respectively. and downstream weighing value The coal loss compensation amount is calculated based on the upstream and downstream weighing values. : ； When the absolute value of the coal loss compensation is greater than the preset compensation threshold, the upstream weighing value is used. The reference weight is used as the reference weight, and the new calibration coefficient is calculated according to the following formula. : ； in, This represents the number of cross-sectional frames included in the cumulative calculation during the calibration period.

7. The non-contact automatic metering calibration method for a coal feeder according to claim 1, characterized in that, In step S6, the replacement of the current calibration coefficient with the new calibration coefficient adopts a smooth update strategy: ； in, The calibration coefficients are as described above. The new calibration coefficient is calculated in step S5. To ensure smooth coefficient updates.

8. The non-contact coal feeder automatic metering calibration method according to claim 1, characterized in that, The preset calibration trigger condition includes at least one of the following conditions: The continuous running time reaches the preset calibration cycle; The changes in the coal quality parameters of the coal fed into the furnace exceed the preset threshold for coal type changes; The continuous measurement deviation exceeds the preset deviation threshold and continues for a preset duration.

9. The non-contact automatic metering calibration method for a coal feeder according to any one of claims 1 to 8, characterized in that, Also includes: The operating environment temperature of the image acquisition device and light source is controlled to a preset constant temperature range to eliminate the effects of temperature drift; as well as The conveyor belt deviation is detected in real time, and when the deviation exceeds a preset deviation threshold, the coordinate offset of the acquisition area of ​​the sequence cross-sectional image is corrected.

10. The non-contact automatic metering calibration method for a coal feeder according to claim 1, characterized in that, In step S1, the light curtain adopts a primary and backup redundant light source structure. When the output intensity of the primary light source decays to below a preset intensity threshold, it automatically switches to the backup light source.

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